SBIR-STTR Award

Wearable sensor devices to measure and improve sleep quality at home
Award last edited on: 5/1/2015

Sponsored Program
SBIR
Awarding Agency
NSF
Total Award Amount
$149,028
Award Phase
1
Solicitation Topic Code
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Principal Investigator
Madhvi Upender

Company Information

Awarables Inc

10513 Rivers Bend Lane
Potomac, MD 20854
   (202) 674-3911
   N/A
   www.awarables.com
Location: Single
Congr. District: 06
County: Montgomery

Phase I

Contract Number: ----------
Start Date: ----    Completed: ----
Phase I year
2014
Phase I Amount
$149,028
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to increase self-awareness, promote health literacy, improve patient-physician communication, and reduce the cost of healthcare. The annual individual and societal costs of sleep loss and sleep disorders are estimated to be in billions of dollars in both direct and indirect costs related to co-morbid medical conditions, hospitalization, accidents, and productivity loss. Wearable, wireless systems are said to be a revolutionary technology for health and wellness management. While this likely exaggerates their impact, we believe that the application of these technologies to specific groups, such as children with ADHD or autism spectrum disorder, will help those individuals and their families address a critical problem in their lives. By extension, one can foresee applications of the technologies to help the elderly and people with depression, schizophrenia, addiction and other mental and physical disorders. The proposed project addresses the need for safe, effective measures for assessing and understanding sleep in the home and promoting sleep literacy among consumers. We propose to provide technology, systems, and support for user-centered sleep healthcare. The first component will focus on Data acquisition (DAQ) using low cost, unobtrusive wearable sensor technology to monitor activity, sound (snoring and speech), heart rate (heart rate variability), respiration rate, pulse transit time, temperature, etc. over 24 hour periods or longer. The DAQ methods will employ mobile technology to support their use at home. The second component will incorporate signal processing and feature extraction tools that employ nonlinear, complex systems analysis to harvest clinically relevant sleep quality, quantity, and health information from variables such as sleep stage transitions and heart rate variability. In addition, development of neurocognitive tests, including reaction time tests similar to psychomotor vigilance tests (PVT), will evaluate the impact of sleep quality and quantity on cognitive performance. These devices and tools will be designed for use by consumers (and clinicians) to assess the effectiveness of treatment systems such as Cognitive Behavior Therapies (CBT) intended to improve sleep

Phase II

Contract Number: ----------
Start Date: ----    Completed: ----
Phase II year
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Phase II Amount
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